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检索条件"任意字段=2023 3rd International Conference on Detection Technology and Intelligence System, DTIS 2023"

共 2101 条记录，以下是371-380 订阅

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LTEDI 2023 - 3rd Workshop on Language technology for Equality, Diversity and Inclusion, associated with the 14th international conference on Recent Advances in Natural Language Processing, RANLP 2023 - Proceedings

LTEDI 2023 - 3rd Workshop on Language Technology for Equalit...

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3rd Workshop on Language technology for Equality, Diversity and Inclusion, LTEDI 2023

ISBN: (纸本)9789544520847

The proceedings contain 47 papers. The topics discussed include: an exploration of zero-shot natural language inference-based hate speech detection;English2BSL: a rule-based system for translating English into British sign language;multilingual models for sentiment and abusive language detection for Dravidian languages;overview of the shared task on detecting signs of depression from social media text;overview of the second shared task on speech recognition for vulnerable individuals in Tamil;overview of second shared task on homophobia and transphobia detection in social media comments;overview of the shared task on hope speech detection for equality, diversity, and inclusion;and evaluating the impact of stereotypes and language combinations on gender bias occurrence in NMT generic systems.

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An Effective Deep CNN Model for Multiclass Brain Tumor detection Using MRI Images and SHAP Explainability 3

An Effective Deep CNN Model for Multiclass Brain Tumor Detec...

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3rd international conference on Electrical, Computer and Communication Engineering, ECCE 2023

作者： Ahmed, Shamim Nobel, Sm Nuruzzaman Ullah, Oli Bangladesh University of Business and Technology Dept of Computer Science and Engineering Bangladesh

ISBN: (纸本)9798350345360

In today's health system, clinical diagnosis has taken on a crucial role. Brain cancer, which is the most serious illness and the main cause of death worldwide, is a significant area of study in the field of medical imaging. Brain cancers must be categorized and found to evaluate the tumors and choose the most appropriate course of treatment for each class. To find brain tumors, numerous imaging modalities are used. However, MRI is frequently utilized since it produces superior images and uses no ionizing radiation. Machine learning's area of deep learning (DL) lately displayed impressive performance, particularly in classification and segmentation issues. We offer an explanation-driven Deep Learning model for the prediction of discrete subtypes of brain tumors (meningioma, glioma, and pituitary) utilizing a brain tumor MRI imaging dataset employing an EfficientNetB0 convolutional neural network (CNN) and Shapley additive explanation (SHAP). The proposed brain tumor detection and classification method surpasses previous methods both visually and numerically, according to an experimental investigation, and achieves an accuracy of 99.84%. The eXplainable Artificial intelligence (XAI) approach (SHAP) is then used to explain the outcome. © 2023 IEEE.

关键词： Magnetic resonance imaging

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Swarm-based Airborne Ground Penetrating Radar for Landmine detection 3

Swarm-based Airborne Ground Penetrating Radar for Landmine D...

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3rd IEEE international conference on Mobile Networks and Wireless Communications, ICMNWC 2023

作者： Sharma, Jayesh Satpathy, R.K. Ray, K.P. Defence Institute of Advanced Technology Dept of Aerospace Engineering Pune India Defence Institute of Advanced Technology Dept of Electronics Engineering Pune India

ISBN: (纸本)9798350317022

Ground Penetrating Radar is a system that uses electromagnetic waves to scan the subsurface for underground targets. It is one of the primary methods used for landmine detection in strategic locations. Land-coupled GPR are constrained by slow speed and the risk of triggering a landmine while scanning. Air-coupled GPRs are restricted by the payload capacity of the single aerial vehicle used. A novel GPR system design is proposed in this paper, which uses the concepts of phased antenna arrays and wireless beamforming. A swarm of Unmanned Aerial Vehicles is used as a platform to carry a phased array GPR for landmine detection applications. It is found that such a system solves the constraints posed by ground-coupled and conventional air-coupled GPR. Simulation results reveal that the designed system gives better performance and provides more than twice the depth of penetration provided by a single UAV-based GPR. © 2023 IEEE.

关键词： antenna array ground penetrating radar swarm uav wireless beamforming

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Role of Artificial intelligence in Haematological Disorder 3

Role of Artificial Intelligence in Haematological Disorder

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3rd international conference on Innovative Sustainable Computational Technologies, CISCT 2023

作者： Guleria, Damini Garg, Vivek Kumar Chandigarh University Department of Medical Lab Technology Mohali India

ISBN: (纸本)9798350303360

Artificial intelligence (AI) is a branch of computer science that uses a computational framework to replicate human brain functions. The primary non-natural neuron was created in 1943, and the primary non-natural neural system (ANN) was applied to hereditary procedures soon afterward. Researchers and scientists have already recognized the potential for a comparable technology in medicine. The capability of this technology to retain and analyses altogether medicinal information consumes it very alluring to complement or perhaps replace clinician in creation a designs. The routine of skilled or knowledge-based organizations in dull scientific use for analysis, healing management, and predictive assessment are examples of requests of artificial intelligence in medicine. New samples contain procedures practical to analysis in, psychiatry, heart illnesses etc. Biomedical applications include protein structure prediction, analysis and clustering of gene expression data, genome sequencing The first AI-based gadgets have been used in hematology to manage routine laboratory data. Created on neural systems expert by information since marginal plasma study, new methods for the differential diagnosis of certain diseases, such as anemias, thalassemia, and leukemia, are now available. © 2023 IEEE.

关键词： Neural networks

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An analysis of the application of artificial intelligence in product interaction design 3

An analysis of the application of artificial intelligence in...

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3rd Guangdong-Hong Kong-Macao Greater Bay Area Artificial intelligence and Big Data Forum, AIBDF 2023

作者： Yu, Ying Ren, Huixian Shenyang jianzhu university Institute of Design and Art Hunnan Shenyang China

ISBN: (纸本)9798400716362

With the advent of the era of artificial intelligence, people’s knowledge and research on artificial intelligence technology system is gradually increasing, and artificial intelligence technology is gradually affecting the development of various fields. In terms of product interaction design, the application of artificial intelligence technology can further enhance user experience. This paper explores the application of AI in product interaction design on the basis of AI research, and further explains how AI technology can be better applied in product interaction design. © 2023 Copyright held by the owner/author(s).

关键词： Artificial intelligence

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Insulator detection of Yolov5 fused with GBAM and α-IOU 3

Insulator detection of Yolov5 fused with GBAM and α-IOU

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3rd IEEE international conference on Electronic technology, Communication and Information, ICETCI 2023

作者： Luo, Xin Chen, Junsun Sun, Guangling Dai, Ziqi Anhui Jianzhu University School of Electronic and Information Engineering Hefei China Anhui Jianzhu University School of Big Data and Statistics Hefei China

ISBN: (纸本)9798350398410

Insulator fault of power line is easy to lead to transmission system fault, so insulator detection system is widely used. Based on this, an improved detection method for Yolov5 is proposed, this method constructs a new network framework through Yolov5. First, the Yolov5 loss function CIoU is improved, and the generalized power transformation is introduced into the existing CIoU loss to optimize the boundary frame regression and improve the accuracy of the boundary frame regression. Then, GBAM attention mechanisms are introduced in each C3 module of the Yolov5 backbone to reduce information dispersion and amplify global interaction features. Finally, create a custom damaged insulator data set. The results show that the network is more accurate and faster than the control group, with an accuracy of 97.42% for insulator defect detection and 4.01 images per second, which is good efficiency and practicality in insulator defect detection. © 2023 IEEE.

关键词： Object detection

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Point Target detection for MAWS Application 3

Point Target Detection for MAWS Application

引用

3rd international conference on Range technology, ICORT 2023

作者： Kumar, Nikhil Gopinathan, Unnikrishnan Kandpal, Neeta Kumar, Ajay Defence Research and Development Organization Instruments Research and Development Establishment Dehradun India

ISBN: (纸本)9781665493314

Distant aerial threats observed from Missile Approach Warning system (MAWS) appear as point targets therefore point target detection is a significant field of research for the defence sector. In the current work, the authors have carried out an analysis of three distinct combinations of algorithms for point target detection: Top Hat Morphology(THM) with a fixed global threshold, THM with adaptive threshold and THM with corner detection. A number of IR video sequences of sky background are recorded with an ultra wide FOV IR sensor and Gaussian blurred point targets with predefined trajectory have been overlaid on this. In this way a synthetic video data-set has been generated. Authors have used three variants of dataset: 14-bit uncompressed, 8-bit linearly compressed and 8-bit non linearly compressed for performance analysis. Probability of detection and false alarms per frame have been considered as performance measure. Analysis for execution time has also been carried out. © 2023 IEEE.

关键词： Morphology

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Research on Fast Steel Surface Deficiency detection system based on FPGA 3

Research on Fast Steel Surface Deficiency Detection System b...

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3rd international conference on Applied Mathematics, Modelling, and Intelligent Computing, CAMMIC 2023

作者： Wang, Yaoyao Liu, Dengfeng School of Artificial Intelligence and Computer Jiangnan University Wuxi214122 China Jiangsu Provincial Engineering Laboratory of Pattern Recognition and Computational Intelligence Jiangnan University Wuxi214122 China

ISBN: (数字)9781510667617

ISBN: (纸本)9781510667600

Convolutional neural network-related applications have now been developed on a variety of platforms, including CPUs, GPUs, and others, but most of them sacrificed energy consumption to achieve good performance. Therefore, in recent years, more and more hot spots have shifted to how to achieve related applications such as low energy consumption research methods. In order to make the steel surface defect detection system meet the requirements of real-time detection, this article proposes that VGG16 is used as the main network to complete the design of the FPGA's rapid detection and identification system for the FPGA. This system conducts software and hard-hard design based on the ZYNQ-7000 platform (1) The design of parallelization of convolution on the PL side The hardware acceleration is achieved by accelerating the data flow design. Each IP core accelerated with the PL end. (2) In the method of quantifying the data, in the case of almost little loss of data accuracy, the use of resources on FPGA films has been greatly reduced to achieve acceleration of algorithms. The final experimental results show that compared with the CPU, this algorithm has increased by 6 times. The power consumption ratio of the CPU platform and the FPGA platform is 12.6, and the power consumption ratio of the GPU platform and the FPGA platform is 38.2, which is more suitable for applications on the embedded platform. © 2023 SPIE.

关键词： Field programmable gate arrays (FPGA)

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Enhancing Credit Card Fraud detection: Analyzing Time and Amount Distributions with Computational intelligence Algorithms 3

Enhancing Credit Card Fraud Detection: Analyzing Time and Am...

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3rd international conference on Ubiquitous Computing and Intelligent Information systems, ICUIS 2023

作者： Rinku Dubey, Ashutosh Kumar Narang, Sushil Kumar Kishore, Neha Chitkara University School of Engineering and Technology Chitkara University Himachal Pradesh India Chitkara University Institute of Engineering and Technology Chitkara University Punjab India University Institute of Engineering and Technology Maharaja Agrasen University Himachal Pradesh India

ISBN: (纸本)9798350306989

Credit card fraud presents a significant risk to both financial institutions and cardholders, necessitating the implementation of robust detection measures. This study focused on evaluating the distributions of time and transaction amounts to enhance the effectiveness of fraud detection. By analyzing distribution patterns, activity anomalies, and trends, it becomes possible to identify fraudulent transactions. Specifically, the amount distribution provides valuable insights into the monetary dimension of fraud, aiding in the identification of suspicious activities. Logistic regression (LR), support vector machines (SVM), and k-nearest neighbors (kNN) were used for the model analysis and evaluation. The results demonstrate that SVM outperforms both LR and kNN, exhibiting high precision and recall rates, as well as an improved F1-measure. In particular, the precision achieved for the no fraud and fraud categories is 0.92 and 0.96, respectively. The corresponding recall rates are 0.96 for the no fraud category and 0.9 for the fraud category. The F1-scores achieved are 0.91 for the no fraud category and 0.93 for the fraud category. Moreover, the average accuracy attained is 0.95. These findings also emphasize the significance of analyzing time and amount distributions and employing suitable model for the effective detection. © 2023 IEEE.

关键词： Logistic regression

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3rd IEEE international conference on ICT in Business Industry and Government, ICTBIG 2023

3rd IEEE International Conference on ICT in Business Industr...

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3rd IEEE international conference on ICT in Business Industry and Government, ICTBIG 2023

ISBN: (纸本)9798350343274

The proceedings contain 253 papers. The topics discussed include: Alzheimer's disease MRI image segmentation based on the enhanced U-Net;optimalization of Tiktok platform for green business digital marketing strategies;evaluative analysis of secure approaches in simulated real-world contexts;advancing early detection of cervical cancer through multi-model intelligent classifiers and computational technique;analysis of approaches for identifying threats in the Internet of Medical Things (IoMT) and exploration of research frontiers;meet the rocket women of chandrayaan-3: pioneers in space exploration;sensor-based networks and the internet of an everything solutions and difficulties;machine learning with artificial intelligence: and towards a broad consensus;smart ticketing and overcrowding control system for public transportation;and harnessing the power of deep learning algorithms for high-accuracy plant disease diagnosis and prediction.

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